THE ROLE

Data is at the heart of how we grow, optimize, and innovate our e-commerce business at Canyon. As a Data Scientist in our Digital department, you build, operationalize, and scale data-driven models on Google Cloud Platform to drive customer lifetime value expansion, margin optimization, marketing mix modeling, and AI-native applications. Your data products will directly impact business operations and commercial decision-making across all global channels. 

YOUR JOB AS PART OF THE CANYON CREW

• Customer Intelligence: Designing and deploying Customer Lifetime Value (CLV) models that integrate customer, transaction, engagement data, and acquisition costs leverages complex enterprise data structures.
• Price Modeling: Building price elasticity algorithms using historical demand, inventory levels, and market signals optimizes gross margins across our bike portfolio.
• Acquisition Channel Optimization: Defining and deploying an advanced Marketing Mix Model (MMM) through Google’s Meridian framework measures and optimizes multi-channel advertising efficiency.
• Personalization Engine: Developing personalization systems for website and marketing touchpoints utilizes customer engagement and preference data.
• Predictive Marketing: Implementing propensity-to-buy and propensity-to-churn models fuels targeted email remarketing as well as predictive lookalike audiences across paid media channels.
• Technical Ownership: Building operational ML workflows in Google Cloud Platform (Gemini Agent Platform, BigQuery, Python) establishes robust pipelines for feature engineering, model tracking, and automated retraining.
• Data Preparation & Collaboration: Supporting data engineer:s hands-on with pipeline setup, data cleaning, and automation in BigQuery and dbt ensures ideal conditions for downstream model training.
• Evaluation & Quality Assurance: Monitoring ML infrastructure and model availability includes implementing version control and maintaining transparent documentation for all data products.
• Stakeholder Management: Partnering directly with commercial lead:s across CRM, Pricing, Sales, Performance Marketing, and E-Commerce translates business challenges into quantitative models with clear commercial targets.

HOW YOU BECOME PART OF THE RACE

• Educational Background: A degree in data science, data analytics, statistics, applied mathematics, or a closely related quantitative field forms your academic foundation.
• Professional Experience: 4+ years of hands-on experience developing, deploying, and validating machine learning models in production environments within e-commerce, retail, or digital industries characterises your background.
• Technical Stack & Tools: Advanced Python proficiency (Scikit-learn, XGBoost, PyTorch/TensorFlow, Pandas), strong SQL skills for extracting data in BigQuery, and practical experience with API integrations and Git version control set your profile apart.
• Cloud & ML Ecosystem: Demonstrated expertise deploying models within Google Cloud Platform (Gemini Agent Platform, BigQuery ML, Meridian, Cloud Run) or equivalent environments (AWS/Azure) shapes your daily execution.
• Statistical Mastery: A solid foundation in supervised and unsupervised learning, time-series forecasting, statistical hypothesis testing, and price sensitivity/elasticity analysis defines your analytical approach.
• Commercial ML Expertise: Proven success delivering commercial ML use cases in e-commerce (CLV, acquisition cost optimization, pricing models, retention, personalization) drives business impact.
• Language Skills: Excellent English communication skills (both spoken and written) enable smooth and effective collaboration across international teams and business functions.